When magnetic resonance (“MR”) examinations are carried out on a person, dielectric resonances cause a considerable spatial inhomogeneity in the transmit (“TX”) B1 field and the receive (“RX”) B1 field, above all in the case of field strengths in excess of two Tesla. As a result, the images generated are not homogeneous but exhibit signal differences even in the case of effectively identical tissue. This is an undesirable effect since a diagnosis may be based on the comparison of spatially separate but identical tissues, for example, between a left side and a right side of a head.
In order to compensate for the spatial inhomogeneity of the transmit (TX) B1 field, the polarization of the B1 field may be modulated. The possibility may therefore exist to influence the polarization by using two separate transmission channels. The use of two channels, however, does not under certain circumstances adequately reduce the problem of the location-dependent changes in contrast produced by the dielectric resonances. A greater number of channels is, however, complicated and technical implementation may be achieved only with difficulty.
An alternative is to use B1-insensitive radio-frequency (“RF”) pulses, but this requires more time in order to carry out a measurement. Furthermore, this method tends to introduce more energy into the patient, for which reason it may, as a general rule, only be used for special purposes.
If the tissue properties were known for each pixel of a acquired image, the MR signal behavior for each pixel may be simulated as a function of the associated B1 value and a signal intensity of a pixel may be interpolated to a corrected value, namely by a Bloch simulation using the measured B1 value and the sequence type used. Since the signal behavior is tissue-dependent, however, this approach is not feasible for human organs.
In order to compensate for the spatial inhomogeneity of the receive B1 field, there is no solution that may be implemented physically because the receive B1 field cannot be measured independently of a spin density. There are however publications that demonstrate a mirror-image relationship between the transmit B1 field and the receive B1 field. This is utilized, for example, by S.-K. Lee, W. T. Dixon in the publication: “In-vivo RF Receiver Sensitivity Measurement Using Phase-Based B1+Mapping on a Reverse-Oriented Subject,” Proc. Intl. Soc. Mag. Reson. Med., 19, p. 4429 (2011), through mirror-image positioning of the object to be measured.
In addition, image filtering may be used in order to allow the images to appear more homogeneous, for example, through high-pass filtering of the images produced. The filtering may, however, also filter out signal differences having a pathological cause, which means that as a general rule this does not represent a meaningful course of action. For example, U.S. Patent Publication No. 2014/0035575 A1 discloses an image filtering of different tissue regions that may theoretically exhibit the same signal intensity.
Approaches are also known, (e.g., from Wang et al., Magnetic Resonance in Medicine, 53, pp. 408-417 (2005)), in order to parameterize a sequence such that there are only slight contrast differences between tissues and to then utilize the sequence for a correction.
In some applications, a combination of multi-contrast measurements is used in order to separate the influence of the transmit and receive B1 effects (see e.g., Marques J P, et al., “MP2RAGE: A self bias-field corrected sequence for improved segmentation and T1-mapping at high field,” Neuroimage 49, Vol. 2, pp. 1271-1281 (2010)). However, this is only possible with the aid of a special excitation sequence, which results in a long scan time and only one contrast type.
EP 1 211 518 A1 discloses a MR imaging method in which the acquisition of the MR data is carried out in accordance with the SENSE method using a plurality of receive coils. The differing spatial sensitivity profiles of the receive coils are utilized for the image reconstruction. If the sensitivity data used for the image reconstruction does not correspond to the spatial location of the receive coils obtaining at image acquisition time, then this results in undesirable image artifacts. The image artifacts are eliminated by automatically adjusting the spatial sensitivity profiles during the image reconstruction.